SYSTEM AND METHOD FOR OPTICAL COHERENCE TOMOGRAPHY A-SCAN DECURVING

    公开(公告)号:US20230363638A1

    公开(公告)日:2023-11-16

    申请号:US18040186

    申请日:2021-08-10

    Applicant: ACUCELA INC.

    CPC classification number: A61B3/102 G01B9/02091

    Abstract: An OCT system for measuring a retina as part of an eye health monitoring and diagnosis system. The OCT system includes an OCT interferometer, where the interferometer comprises a light source or measurement beam and a scanner for moving the beam on the retina of a patient's eye, and a processor configured to execute instructions to cause the scanner to move the measurement beam on the retina in a scan pattern. Measurement data may be processed using a decurving process to enhance the resolution of the ILM layer and provide improved determinations of retinal thickness.

    SCAN PATTERN AND SIGNAL PROCESSING FOR OPTICAL COHERENCE TOMOGRAPHY

    公开(公告)号:US20220257112A1

    公开(公告)日:2022-08-18

    申请号:US17662582

    申请日:2022-05-09

    Applicant: ACUCELA INC.

    Abstract: An OCT system for measuring a retina as part of an eye health monitoring and diagnosis system. The OCT system includes an OCT interferometer, where the interferometer comprises a light source or measurement beam and a scanner for moving the beam on the retina of a patient's eye, and a processor configured to execute instructions to cause the scanner to move the measurement beam on the retina in a scan pattern. The scan pattern is a continuous pattern that includes a plurality of lobes. The measurement beam may be caused to move on the retina by the motion of a mirror that intercepts and redirects the measurement beam. The mirror position may be altered by the application of a drive signal to one or more actuators that respond to the drive signal by rotating the mirror about an axis or axes.

    ARTIFICIAL INTELLIGENCE FOR EVALUATION OF OPTICAL COHERENCE TOMOGRAPHY IMAGES

    公开(公告)号:US20220084197A1

    公开(公告)日:2022-03-17

    申请号:US17444806

    申请日:2021-08-10

    Applicant: ACUCELA INC.

    Abstract: A neural network is trained to segment interferogram images. A first plurality of interferograms are obtained, where each interferograms corresponds to data acquired by an OCT system using a first scan pattern, annotating each of the plurality of interferograms to indicate a tissue structure of a retina, training a neural network using the plurality of interferograms and the annotations, inputting a second plurality of interferograms corresponding to data acquired by an OCT system using a second scan pattern and obtaining an output of the trained neural network indicating the tissue structure of the retina that was scanned using the second scan pattern. The system and methods may instead receive a plurality of A-scans and output a segmented image corresponding to a plurality of locations along an OCT scan pattern.

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